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Onutoa
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1_6e-3_1_0.5

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - super_glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: 1_6e-3_1_0.5
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # 1_6e-3_1_0.5
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+
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+ This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4885
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+ - Accuracy: 0.7401
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.006
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 11
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.9248 | 1.0 | 590 | 0.7400 | 0.3786 |
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+ | 0.8836 | 2.0 | 1180 | 0.7971 | 0.3914 |
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+ | 0.8513 | 3.0 | 1770 | 0.6664 | 0.6217 |
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+ | 0.7488 | 4.0 | 2360 | 0.7384 | 0.6217 |
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+ | 0.729 | 5.0 | 2950 | 1.0125 | 0.6217 |
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+ | 0.7097 | 6.0 | 3540 | 0.7106 | 0.5046 |
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+ | 0.6521 | 7.0 | 4130 | 0.5533 | 0.6098 |
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+ | 0.6704 | 8.0 | 4720 | 0.4852 | 0.6587 |
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+ | 0.6271 | 9.0 | 5310 | 0.5153 | 0.6850 |
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+ | 0.6134 | 10.0 | 5900 | 0.4555 | 0.6948 |
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+ | 0.5702 | 11.0 | 6490 | 0.4732 | 0.6716 |
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+ | 0.5428 | 12.0 | 7080 | 0.4548 | 0.6963 |
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+ | 0.5681 | 13.0 | 7670 | 0.4534 | 0.6859 |
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+ | 0.5238 | 14.0 | 8260 | 0.6556 | 0.6725 |
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+ | 0.5103 | 15.0 | 8850 | 0.5050 | 0.7110 |
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+ | 0.5004 | 16.0 | 9440 | 0.4638 | 0.6813 |
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+ | 0.4614 | 17.0 | 10030 | 0.4935 | 0.7113 |
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+ | 0.4702 | 18.0 | 10620 | 0.4570 | 0.7040 |
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+ | 0.4305 | 19.0 | 11210 | 0.4871 | 0.7190 |
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+ | 0.4402 | 20.0 | 11800 | 0.5026 | 0.6722 |
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+ | 0.4035 | 21.0 | 12390 | 0.4476 | 0.7208 |
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+ | 0.3907 | 22.0 | 12980 | 0.6030 | 0.6367 |
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+ | 0.3686 | 23.0 | 13570 | 0.4396 | 0.7131 |
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+ | 0.3765 | 24.0 | 14160 | 0.4589 | 0.7180 |
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+ | 0.3709 | 25.0 | 14750 | 0.4440 | 0.7107 |
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+ | 0.3446 | 26.0 | 15340 | 1.0145 | 0.5728 |
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+ | 0.3433 | 27.0 | 15930 | 0.6213 | 0.6627 |
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+ | 0.331 | 28.0 | 16520 | 0.4566 | 0.7144 |
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+ | 0.3373 | 29.0 | 17110 | 0.5484 | 0.7284 |
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+ | 0.3117 | 30.0 | 17700 | 0.6371 | 0.6648 |
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+ | 0.2988 | 31.0 | 18290 | 0.7013 | 0.7089 |
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+ | 0.2928 | 32.0 | 18880 | 0.4553 | 0.7281 |
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+ | 0.297 | 33.0 | 19470 | 0.5225 | 0.6976 |
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+ | 0.2808 | 34.0 | 20060 | 0.4951 | 0.7343 |
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+ | 0.2735 | 35.0 | 20650 | 0.5188 | 0.7095 |
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+ | 0.2624 | 36.0 | 21240 | 0.4961 | 0.7367 |
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+ | 0.2642 | 37.0 | 21830 | 0.4731 | 0.7254 |
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+ | 0.2548 | 38.0 | 22420 | 0.4635 | 0.7260 |
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+ | 0.2575 | 39.0 | 23010 | 0.4896 | 0.7073 |
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+ | 0.244 | 40.0 | 23600 | 0.5605 | 0.7358 |
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+ | 0.2472 | 41.0 | 24190 | 0.6450 | 0.7266 |
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+ | 0.2433 | 42.0 | 24780 | 0.4922 | 0.7367 |
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+ | 0.2312 | 43.0 | 25370 | 0.5115 | 0.7269 |
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+ | 0.2355 | 44.0 | 25960 | 0.4879 | 0.7388 |
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+ | 0.2204 | 45.0 | 26550 | 0.5023 | 0.7355 |
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+ | 0.2223 | 46.0 | 27140 | 0.4976 | 0.7355 |
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+ | 0.22 | 47.0 | 27730 | 0.5051 | 0.7364 |
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+ | 0.2056 | 48.0 | 28320 | 0.4973 | 0.7205 |
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+ | 0.2166 | 49.0 | 28910 | 0.5008 | 0.7180 |
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+ | 0.2129 | 50.0 | 29500 | 0.5323 | 0.7382 |
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+ | 0.1973 | 51.0 | 30090 | 0.5689 | 0.6908 |
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+ | 0.2025 | 52.0 | 30680 | 0.4855 | 0.7367 |
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+ | 0.1977 | 53.0 | 31270 | 0.5230 | 0.7211 |
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+ | 0.1946 | 54.0 | 31860 | 0.5969 | 0.7333 |
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+ | 0.2063 | 55.0 | 32450 | 0.5340 | 0.7098 |
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+ | 0.1967 | 56.0 | 33040 | 0.5589 | 0.7361 |
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+ | 0.1793 | 57.0 | 33630 | 0.5207 | 0.7358 |
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+ | 0.1872 | 58.0 | 34220 | 0.4926 | 0.7394 |
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+ | 0.1831 | 59.0 | 34810 | 0.5265 | 0.7434 |
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+ | 0.1808 | 60.0 | 35400 | 0.5113 | 0.7407 |
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+ | 0.1892 | 61.0 | 35990 | 0.4972 | 0.7416 |
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+ | 0.1795 | 62.0 | 36580 | 0.5121 | 0.7391 |
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+ | 0.172 | 63.0 | 37170 | 0.4857 | 0.7321 |
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+ | 0.176 | 64.0 | 37760 | 0.5014 | 0.7232 |
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+ | 0.1763 | 65.0 | 38350 | 0.5061 | 0.7370 |
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+ | 0.1753 | 66.0 | 38940 | 0.4840 | 0.7358 |
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+ | 0.1716 | 67.0 | 39530 | 0.5262 | 0.7361 |
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+ | 0.1675 | 68.0 | 40120 | 0.4844 | 0.7324 |
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+ | 0.1647 | 69.0 | 40710 | 0.5357 | 0.7440 |
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+ | 0.1702 | 70.0 | 41300 | 0.4852 | 0.7394 |
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+ | 0.1666 | 71.0 | 41890 | 0.4749 | 0.7391 |
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+ | 0.162 | 72.0 | 42480 | 0.5616 | 0.7385 |
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+ | 0.1546 | 73.0 | 43070 | 0.5089 | 0.7352 |
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+ | 0.1525 | 74.0 | 43660 | 0.5315 | 0.7382 |
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+ | 0.1595 | 75.0 | 44250 | 0.5300 | 0.7419 |
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+ | 0.1555 | 76.0 | 44840 | 0.5664 | 0.7407 |
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+ | 0.1604 | 77.0 | 45430 | 0.5057 | 0.7416 |
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+ | 0.1584 | 78.0 | 46020 | 0.5008 | 0.7355 |
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+ | 0.1574 | 79.0 | 46610 | 0.5206 | 0.7398 |
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+ | 0.1552 | 80.0 | 47200 | 0.5176 | 0.7361 |
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+ | 0.1501 | 81.0 | 47790 | 0.4955 | 0.7376 |
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+ | 0.1492 | 82.0 | 48380 | 0.5001 | 0.7391 |
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+ | 0.1508 | 83.0 | 48970 | 0.4963 | 0.7379 |
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+ | 0.1463 | 84.0 | 49560 | 0.5148 | 0.7413 |
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+ | 0.1449 | 85.0 | 50150 | 0.4868 | 0.7349 |
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+ | 0.1489 | 86.0 | 50740 | 0.5012 | 0.7419 |
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+ | 0.1415 | 87.0 | 51330 | 0.4963 | 0.7321 |
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+ | 0.145 | 88.0 | 51920 | 0.5046 | 0.7291 |
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+ | 0.1375 | 89.0 | 52510 | 0.5011 | 0.7416 |
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+ | 0.1387 | 90.0 | 53100 | 0.5041 | 0.7440 |
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+ | 0.1428 | 91.0 | 53690 | 0.4940 | 0.7425 |
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+ | 0.1442 | 92.0 | 54280 | 0.4912 | 0.7401 |
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+ | 0.139 | 93.0 | 54870 | 0.5014 | 0.7428 |
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+ | 0.1406 | 94.0 | 55460 | 0.4919 | 0.7391 |
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+ | 0.1387 | 95.0 | 56050 | 0.5063 | 0.7446 |
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+ | 0.1368 | 96.0 | 56640 | 0.4902 | 0.7410 |
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+ | 0.1391 | 97.0 | 57230 | 0.4947 | 0.7407 |
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+ | 0.136 | 98.0 | 57820 | 0.4922 | 0.7413 |
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+ | 0.133 | 99.0 | 58410 | 0.4926 | 0.7394 |
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+ | 0.1379 | 100.0 | 59000 | 0.4885 | 0.7401 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3